Sample observation method and sample observation device

ABSTRACT

An inspection method uses a charged particle microscope to observe a sample and view a defect site or a circuit pattern. A plurality of images is detected by a plurality of detectors and a mixed image is generated by automatically adjusting and mixing weighting factors required when the plurality of images are synthesized with each other. The sample is irradiated and scanned with a charged particle beam so that the plurality of detectors arranged at different positions from the sample detects a secondary electron or a reflected electron generated from the sample. The mixed image is generated by mixing the plurality of images of the sample with each other for each of the plurality of detectors, which are obtained by causing each of the plurality of detectors arranged at the different positions to detect the secondary electron or the reflected electron. The generated mixed image is displayed on a screen.

TECHNICAL FIELD

The present invention relates to a method and a device for observing adefect or a circuit pattern appearing while semiconductor wafers aremanufactured, and more particularly relates to a device provided with amethod and means for outputting an image from which the defect or thecircuit pattern is highly visible by using an image obtained from aplurality of detectors included in a charged particle microscope.

BACKGROUND ART

When the semiconductor wafers are manufactured, it is important toquickly start a manufacturing process and to shift to a high-yieldmass-production system at an early stage in order to ensureprofitability. For this purpose, various inspection/measurement devicesare introduced to manufacturing lines.

As a representative inspection device, an optical wafer inspectiondevice is known. For example, JP-A-2000-105203 (PTL 1) discloses atechnique for inspecting the defect in such a way that an optical imageof a wafer surface is captured using bright field illumination and iscompared with an image of a non-defective site (for example, an image ofan adjacent chip). However, according to this optical inspection device,a resolution limit of an acquired image is approximately several hundrednanometers due to the influence of the illumination wavelength.Accordingly, it is possible to detect only whether or not the defect ispresent in the order of several tens of nanometers on the wafer.Consequently, in a case where the defect has to be analyzed in detail,it is necessary to separately provide a defect observation device havinghigher imaging resolution.

The defect observation device is a device which outputs an image afterimaging a defect position on the wafer with high resolution using anoutput of an inspection device. An observation device using a scanningelectron microscope (SEM) (hereinafter, referred to as a review SEM) iswidely used. Observation work needs to be automated in mass productionlines of semiconductors, and the review SEM is provided with a defectimage automatic collection process (ADR: Automatic Defect Review) whichautomatically collects images at the defect position in a sample. Errorsare included in defect position coordinates (coordinate informationindicating the defect position on the sample) output by the inspectiondevice. Accordingly, ADR is provided with a function to obtain anobservation-purpose image by re-detecting the defect from an image inwhich the defect position coordinates output by the inspection deviceare mainly imaged using a wide field of view and by imaging there-detected defect position at high magnification.

As a defect detection method from an SEM image, an image obtained byimaging a region having a circuit pattern the same as that of a defectsite is used as a reference image so that the reference image iscompared with an image obtained by imaging the defect site.JP-A-2001-189358 (PTL 2) discloses this method for detecting the defect.In addition, JP-A-2007-40910 (PTL 3) discloses a method for detectingthe defect from one image obtained by imaging the defect site. Inaddition, JP-A-2013-168595 (PTL 7) discloses a method for recognizing acircuit pattern region from a captured image.

Many types of structures are used for the circuit patterns formed on thesemiconductor wafer, and the defects appear in various types and atvarious positions. In order to improve visibility of the circuitpatterns having various structures and various types of defects, it isan effective way to cause a plurality of detectors to detect electronsemitted from a sample at different emission angles or with differentemission energies. For example, JP-A-2012-186177 (PTL 4) discloses thatinformation on target irregularities can be recognized by detecting anddiscriminating the electrons generated from the sample, based on anelevation angle and an azimuth angle of the emitted electrons. Inaddition, JP-A-1-304647 (PTL 5) discloses a method for detecting thedefect by using the plurality of detectors arranged by dividingreflected electrons emitted in each direction. In addition,JP-A-2013-232435 (PTL 6) discloses a method for improving a contrast ofa lower layer pattern in a multilayer by synthesizing detector imagesobtained from the plurality of detectors.

CITATION LIST Patent Literature

PTL 1: JP-A-2000-105203

PTL 2: JP-A-2001-189358

PTL 3: JP-A-2007-40910

PTL 4: JP-A-2012-186177

PTL 5: JP-A-1-304647

PTL 6: JP-A-2013-232435

PTL 7: JP-A-2013-168595

SUMMARY OF INVENTION Technical Problem

As described above, in order to improve the visibility of the circuitpatterns having various structures or various defects, it is aneffective way to cause many detectors to detect various electrons whichare generated at different emission angles or with different emissionenergies from the sample. However, if the number of detectors increases,the number of images to be viewed for defect observation increases,thereby laying an increasing burden on a user. Therefore, an image fromwhich the defect or the circuit pattern is highly visible needs to beoutput by mixing a plurality of obtained detector images with eachother. Particularly, in a case of ADR, a defect type to be imaged or asurrounding circuit pattern structure varies depending on each targetdefect. Therefore, it is necessary to automatically optimize a synthesismethod for each defect point.

PTL 5 discloses a method in which a weighting factor at the time ofmixing the images is automatically adjusted in accordance with a beamscanning direction. However, PTL 5 does not disclose a method forautomatically adjusting the weighting factor in view of the visibilityof the defect site or the circuit pattern. PTL 6 discloses a method inwhich the weighting factor at the time of mixing the images isautomatically adjusted in accordance with an edge direction of thecircuit pattern obtained from design information. However, PTL 6 doesnot disclose the method for automatically adjusting the weighting factorin view of the visibility of the defect site.

The present invention is made in order to solve the above-describedproblems in the related art. In view of visibility of a defect site or acircuit pattern from a plurality of images detected by a plurality ofdetectors, the present invention aims to provide a sample observationmethod and a sample observation device in which a mixed image can begenerated by automatically adjusting and mixing weighting factorsrequired when the plurality of images are mixed (synthesized) with eachother.

Solution to Problem

In order to solve the above-described problems, the present inventionprovides a method for using a charged particle microscope to observe asample. The method includes causing a plurality of detectors arranged atdifferent positions from the sample to detect a secondary electron or areflected electron generated from the sample by irradiating and scanningthe sample with a charged particle beam, generating a mixed image bymixing a plurality of images of the sample with each other for each ofthe plurality of detectors, which are obtained in such a way that eachof the plurality of detectors arranged at the different positionsdetects the secondary electron or the reflected electron, and displayingthe generated mixed image on a screen.

In addition, in order to solve the above-described problems, the presentinvention provides a method for using a charged particle microscope toobserve a sample. The method includes causing a plurality of detectorsarranged at different positions from the sample to detect a secondaryelectron or a reflected electron generated from a first region of thesample by irradiating and scanning the first region with a chargedparticle beam, generating a plurality of images of the first region foreach of the plurality of detectors, based on a signal obtained bycausing each of the plurality of detectors arranged at the differentpositions to detect the secondary electron or the reflected electron,calculating a mixing parameter serving as each weight of the pluralityof generated images of the first region for each of the plurality ofdetectors, causing the plurality of detectors arranged at the differentpositions from the sample to detect the secondary electron or thereflected electron generated from a second region by irradiating andscanning the second region inside the first region on the sample withthe charged particle beam, generating a plurality of images of thesecond region for each of the plurality of detectors with highermagnification than that of the plurality of images of the first region,based on a signal obtained by causing each of the plurality of detectorsarranged at the different positions to detect the secondary electron orthe reflected electron, generating a mixed image with high magnificationin such a way that the plurality of generated images of the secondregion are mixed with each other using the calculated mixing parameter,and displaying the generated mixed image with high magnification on ascreen.

Furthermore, in order to solve the above-described problems, the presentinvention provides a device for using a charged particle microscope toobserve a sample. The device includes the charged particle microscopethat includes a plurality of detectors arranged at different positionsfrom the sample so that the plurality of detectors detect a secondaryelectron or a reflected electron generated from the sample byirradiating and scanning the sample with a charged particle beam, animage generation unit that generates images of the sample for each ofthe plurality of detectors, based on a signal obtained by causing eachof the plurality of detectors arranged at the different positions of thecharged particle microscope to detect the secondary electron or thereflected electron, a mixed image generation unit that generates a mixedimage by mixing the images of the sample which are generated by theimage generation unit for each of the plurality of detectors, and adisplay unit that displays the mixed image generated by the mixed imagegeneration unit.

Advantageous Effects of Invention

According to the present invention, a defect observation deviceincluding a plurality of detectors can output an image from which adefect and a circuit pattern are highly visible, thereby enabling a userto reduce the burden when the user carries out image viewing work.

In addition, according to the present invention, in view of visibilityof a defect site or a circuit pattern from a plurality of imagesdetected by a plurality of detectors, a mixed image can be generated byautomatically adjusting and mixing weighting factors required when theplurality of images are mixed (synthesized) with each other, therebyenabling the user to reduce the burden when the user carries out theimage viewing work. The problems, configurations, and advantageouseffects other than those described above will be clarified by thedescription of the following embodiments.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating a schematic configuration of asample observation device according to Embodiment 1 of the presentinvention.

FIG. 2 is a block diagram illustrating a schematic configuration of acontrol unit, a storage unit, and a calculation unit in the sampleobservation device according to Embodiment 1 of the present invention.

FIG. 3A is a perspective view around a stage which illustrates anarrangement example of detectors in the sample observation deviceaccording to Embodiment 1 of the present invention.

FIG. 3B is a plan view around the stage including the detectors whichillustrates the arrangement example of the detectors in the sampleobservation device according to Embodiment 1 of the present invention.

FIG. 3C is a front view around the stage including the detectors whichillustrates the arrangement example of the detectors in the sampleobservation device according to Embodiment 1 of the present invention.

FIG. 4 is a sectional view illustrating a position relationship betweenan emission angle of a secondary electron or a reflected electron andthe detector when a sample surface having a convex pattern is scannedwith an electron beam in the sample observation device according toEmbodiment 1 of the present invention, and is a view in which adetection signal pattern output from each detector is illustrated usinga graph.

FIG. 5 is a plan view illustrating a position relationship between thesample surface having the convex pattern and the detector in the sampleobservation device according to Embodiment 1 of the present invention,and is a view in which the detection signal pattern output from eachdetector when the sample surface is scanned with the electron beam isillustrated using a graph.

FIG. 6 is a flowchart illustrating a main flow of an observation processaccording to Embodiment 1 of the present invention.

FIG. 7 is a flowchart illustrating a mixed image generation processaccording to Embodiment 1 of the present invention.

FIG. 8 is a flowchart illustrating a defect information extractionprocess according to Embodiment 1 of the Present invention.

FIG. 9 is a distribution map illustrating a pixel value distributionexample of difference images corresponding to the respective detectorsaccording to Embodiment 1 of the present invention.

FIG. 10 is a flowchart illustrating the defect information extractionprocess according to Embodiment 1 of the present invention.

FIG. 11 is a view illustrating an example of a correspondence tablebetween an appearance characteristic condition and a weighting factoraccording to Embodiment 1 of the present invention.

FIG. 12A illustrates an example in which weighting factors are overlaidand displayed on an image according to Embodiment 1 of the presentinvention, and is a front view of a screen which displays an example inwhich the weighting factors are displayed using character information.

FIG. 12B illustrates an example in which the weighting factors areoverlaid and displayed on the image according to Embodiment 1 of thepresent invention, and is a front view of a screen which displays anexample in which the weighting factors are displayed using a radarchart.

FIG. 12C illustrates an example in which the weighting factors areoverlaid and displayed on the image according to Embodiment 1 of thepresent invention, and is a front view of a screen which displays anexample in which the weighting factors are displayed using a bar graph.

FIG. 13 is a flowchart illustrating a mixed image generation processaccording to Embodiment 2 of the present invention.

FIG. 14A illustrates a detector image according to Embodiment 2 of thepresent invention.

FIG. 14B is a view illustrating a result obtained by discriminating thedetector image into a plurality of regions according to Embodiment 2 ofthe present invention.

FIG. 15 is a table illustrating an example of a mixing parametercalculated for each region according to Embodiment 2 of the presentinvention.

FIG. 16 is a flowchart illustrating an ADR process flow according toEmbodiment 3 of the present invention.

FIG. 17 is a view illustrating a relationship between an input image andan output image in an image mixing process performed by an image mixingprocess unit according to Embodiment 1 of the present invention.

DESCRIPTION OF EMBODIMENTS

The present invention provides a defect observation device including aplurality of detectors. The device can output an image from which adefect and a circuit pattern are highly visible, thereby enabling a userto reduce the burden when the user carries out image viewing work.

In addition, the present invention is made in view of visibility of adefect site or a circuit pattern from a plurality of images detected bya plurality of detectors. According to the present invention, a mixedimage (synthesized image) can be generated by automatically adjustingand mixing (synthesizing) weighting factors required when the pluralityof images are mixed (synthesized) with each other, thereby enabling auser to reduce the burden when the user carries out image viewing work.

Hereinafter, embodiments according to the present invention will bedescribed with reference to the drawings. The present invention is notlimited to the embodiments described below, and includes variousmodifications. The embodiments are described below in detail in order tofacilitate the understanding of the present invention, and are notnecessarily limited to those having all configurations described herein.In addition, the configurations of one embodiment can be partiallysubstituted with the configurations of the other embodiment. Inaddition, the configurations of the other embodiment can be added to theconfigurations of one embodiment. Alternatively, the configurations ofthe respective embodiments can partially have additions, omissions, orsubstitutions of other configurations.

Embodiment 1

Hereinafter, a defect observation device according to the presentinvention will be described. In the present embodiment, an observationdevice including a scanning electron microscope (SEM) will be describedas a target. However, an imaging device according to the presentinvention may be a device other than SEM, and may be an imaging deviceusing a charged particle such as ion.

FIG. 1 illustrates an overall configuration of the device according tothe present invention. The device includes SEM 101 for capturing animage, a control unit 102 for performing overall control, a storage unit103 for storing information in a magnetic disk or a semiconductormemory, a calculation unit 104 for performing calculation in accordancewith a program, an external storage medium input/output unit 105 forinputting and outputting information to and from an external storagemedium connected to the device, a user interface unit 106 forcontrolling the input/output of user's information, and a networkinterface unit 107 for communicating with other devices via a network.An input/output terminal 113 including a keyboard, a mouse, or a displayis connected to the user interface unit 106.

SEM 101 is configured to include a movable stage 109 for mounting asample wafer 108 thereon, an electron source 110 for irradiating thesample wafer 108 with an electron beam (primary electron beam) 1101, anda detector 111 for detecting a secondary electron or a reflectedelectron generated from the sample wafer. In addition, SEM includes anelectron lens (not illustrated) for converging the electron beam ontothe sample, a deflector (not illustrated) for scanning the sample waferwith the electron beam, and an imaging unit 112 for digitally convertinga signal transmitted from the detector 111 so as to generate a digitalimage. These are connected to each other via a bus 114, and can mutuallyexchange information.

FIG. 2 illustrates a configuration of a control unit 102, a storage unit103, and a calculation unit 104. The control unit 102 includes a wafertransport control unit 201 for controlling transport of the sample wafer108, a stage control unit 202 for controlling the stage, abeam shiftcontrol unit 203 for controlling an irradiation position of the electronbeam, and a beam scanning control unit 204 for controlling scanningusing the electron beam.

The storage unit 103 includes an image storage unit 205 for storingacquired image data, a recipe storage unit 206 for storing imagingconditions (for example, an acceleration voltage of the primary electronbeam 1101, a probe current of the detector 111, the number of addedframes of the captured image, and a size of an imaging field of view) orprocess parameters, and a coordinate storage unit 207 for storingcoordinates of an imaging location. In addition, the storage unit 103includes a memory region (not illustrated) for temporarily storingcalculation results.

The calculation unit 104 includes a defect information extraction unit208 for extracting defect information from a detector image, adifference image calculation unit 209 for calculating a differencebetween two images, a difference value distribution informationcalculation unit 210 for calculating distribution information ofdifference values, a mixing parameter calculation unit 211 fordetermining a mixing ratio or a mixing method of the images, an imagemixing process unit 212 for mixing the detector images detected by eachdetector using the information on the determined mixing ratio of theimages, a defect region recognition unit 213 for recognizing a defectregion in the mixed image, and a circuit pattern region recognition unit214 for recognizing a circuit pattern region in the mixed image. Thedefect information extraction unit 208, the difference image calculationunit 209, the difference value distribution information calculation unit210, and the mixing parameter calculation unit 211 may be configured toserve as hardware designed so as to perform each calculation.Alternatively, a configuration may adopted in which all of these aremounted as software and are executed using a general-purpose calculationdevice (for example, CPU or GPU).

A method for acquiring an image at designated coordinates will bedescribed.

First, the wafer 108 serving as a measurement target is installed on thestage 109 by a robot arm (not illustrated) controlled by the wafertransport control unit 201. Next, the stage 109 is moved by the stagecontrol unit 202 so that an imaging field of view is included in anirradiation range of the electron beam 1101. At this time, in order toabsorb a movement error of the stage, a stage position is measured bymeans (not illustrated), and a beam irradiation position is adjusted soas to cancel the movement error by the beam shift control unit 203. Theelectron beam 1101 is emitted from the electron source 110, and is usedin scanning the sample wafer 108 within the imaging field of view by thebeam scanning control unit 204. The secondary electron or the reflectedelectron generated from the sample wafer 108 irradiated with theelectron beam 1101 is detected by the plurality of detectors 111, and isdigitally imaged for each detector through the imaging unit 112. Thecaptured image is stored in the image storage unit 205 together withsupplementary information such as imaging conditions, imaging dates andtimes, and imaging coordinates.

An arrangement of the plurality of detectors 111 will be described withreference to FIG. 3. FIGS. 3A to 3C illustrate a case where detectors301 to 305 are used as the plurality of detectors 111, and schematicallyillustrate a position relationship between the detectors 301 to 305 andthe sample 108. FIG. 3A is a perspective view, FIGS. 3B and 3C are aplan view and a front view which are respectively viewed in a z-axisdirection and a y-axis direction (the detector 305 is not illustrated).Here, the detectors 301 to 304 represent a plurality of detectorsconfigured to selectively detect an electron (mainly, a reflectedelectron) having a specific emission angle. For example, the detector301 represents a detector for detecting the electron emitted from thesample wafer 108 in a y-direction. As the detector, a split type ofdetectors as disclosed in PTL 5 may be used. In addition, the detector305 represents a detector for detecting the secondary electron emittedfrom the sample. Hereinafter, for the sake of simplified description, adevice including five detectors illustrated in the drawing will bedescribed as an example. However, the present invention is applicable tothose other than the detector arrangement, and is also applicable to acase where the number of the detectors increases.

A relationship between an electron emission angle and a detection signalwill be described with reference to FIG. 4. When the primary electronbeam 1101 emitted from an electron gun 110 reaches the surface of thesample 108, if the sample is flat like a position 401, the secondaryelectron 1102 or the reflected electron 1103 is emitted in alldirections (arrows in FIG. 4). Therefore, signal strength isapproximately equalized in each detector. In a case where the sample isnot flat, each angle of the emitted secondary electron 1102 or thereflected electron 1103 is deflected.

For example, at position 402, the electrons emitted leftward around theirradiation position of the primary electron beam 1101 increase comparedto a case where the sample 108 is flat. Accordingly, the detectionsignal of the detector 303 disposed on the left side is strengthened. Onthe other hand, the emitted electrons decrease on the right side.Accordingly, the detection signal of the detector 304 disposed on theright side is weakened. At the position 403, the sample 108 is flat.However, the emitted electrons are blocked by irregularities 410adjacent thereto. Accordingly, the electrons arriving at the detector303 disposed on the left side decrease, and the detection signal isweakened.

In this way, in the detectors 301 to 304 (refer to FIG. 3A) configuredto selectively detect the electron having a specific emission angle, dueto the irregularities 410 on the surface of the sample 108, imagedensity is generated depending on the position of the detectors 301 to304. These detector images are called shadow images, since the imageslook like a shadow as if the light is emitted in the detector directionon the images. The detector 305 located above mainly detects thesecondary electrons, and the image density is generated due to adifference in the emission amounts of the secondary electrons which iscaused by the edge effect of the pattern formed on the sample 108. FIG.4 illustrates signal profiles 404 to 406, which schematically representthe output of the respective detectors 303 to 305. In the graph on thelower side of FIG. 4, the vertical axis indicates the intensity of thesignal output from each detector, and the horizontal axis indicates theposition on the sample.

FIG. 5 is a view schematically illustrating the detection signal of therespective detectors 301 to 305 in a case where a defect site 551 havinga concave shape and a circuit pattern 552 having a convex shape areimaged using SEM 101 (A graph 501 having a sectional shape represents asectional profile between (a) and (b) in an image 550, and a graph 502having a sectional shape represents a sectional profile between (c) and(d) in the image 550).

In the defect site 551 of this example, a recess appears along thex-direction of the image 550. Accordingly, in the detectors 301 and 302arranged in the y-direction of the image, as illustrated in the signalprofiles 511 and 512, a density contrast 510 appears in a wide range ofthe defect site 551. However, in the detectors 303 and 304 arranged inthe x-direction of the image 550, as illustrated in the signal profiles513 and 514, the density contrast 510 does not appear in only both endsof the defect site 551. Therefore, with regard to the defect site 551,the shadow becomes obvious in the detector image formed from the signalprofiles 511 and 512 of the detectors 301 and 302 arranged in they-direction of the image, thereby allowing high visibility.

On the other hand, with regard to the circuit pattern 552 formed alongthe y-direction, a reversed phenomenon tends to appear. In the detectorimage formed from the signal profiles 513 and 514 of the detectors 303and 304 arranged in the x-direction of the image 550, the Visibilitybecomes higher.

In this way, in a case where the plurality of defect sites 551 and thecircuit pattern 552 are included in a plane of the image 550, thedetector whose target visibility becomes higher may vary in some cases.Therefore, for example, in order to obtain a highly visible image of thedefect site 551, it is necessary to perform the followings. Theinformation relating to the visibility of the defect site 551(hereinafter referred to as defect information) is extracted from thedetector images formed by the respective signal profile 511 to 515 foreach of the detectors 301 to 305. Based on the information, the highlyvisible detector image is selected, or the image is generated by mixing(synthesizing) the plurality of detector images obtained from each ofthe signal profiles 511 to 515 of the respective detectors 301 to 305. Aspecific method will be subsequently described below.

FIG. 6 illustrates a main flowchart of an observation process accordingto the present invention. First, the sample wafer 108 serving as anobservation target is loaded on the stage 109 (S601), and a recipestoring image capturing conditions (an acceleration voltage, a probecurrent, and the number of added frames) and image processing conditionsis read from the recipe storage unit 206 so as to set an electronoptical system in accordance with the read conditions (S602). Next,coordinates of the observation target stored in the coordinate storageunit 207 is read (S603).

The subsequent processes S604 to S607 are performed for each of the readthe coordinates of the observation target. First, the movable stage 109is moved using the stage control unit 202 so that the coordinates of theobservation target are included in an imaging field of view (S604). Thebeam scanning control unit 204 is used so that the inside of the imagingfield of view is scanned with the primary electron beam 1101. Thesecondary electron or the reflected electron emitted from the samplewafer 108 is detected by the plurality of detectors 111. The signalsdetected by the plurality of detectors 111 are respectively convertedinto images by the imaging unit 112 so as to obtain a plurality of thedetector images (S605). A mixed image (synthesized image) is generatedfrom the plurality of acquired detector image by the image mixingprocess unit 212 (S606), and the generated mixed image (synthesizedimage) is output (S607).

Details of a mixed image generation process (S606) for generating themixed image (synthesized image) will be described with reference to FIG.7. As previously described, in order to generate a highly visible imageof the defect site, it is necessary to extract defect information fromthe detector image obtained by each detector. Therefore, the defectinformation is extracted from the detector image by the defectinformation extraction unit 208 (S701). Next, based on the extracteddefect information, the mixing parameter calculation unit 211 calculatesa mixing parameter which improves the visibility of the defect site(S702). Based on the calculated mixing parameter, the image mixingprocess unit 212 mixes the images with each other (S703). Hereinafter,details of each process in S701 to S703 will be described.

First, details of a defect information extraction process (S701)performed by the defect information extraction unit 208 will bedescribed. FIG. 8 illustrates a calculation flowchart of differencevalue distribution information which is one of the defect information.The difference value distribution information indicates a relationshipbetween density values of the respective detectors by using a differenceimage between a defect image and a reference image. In order to obtainthe difference value distribution information, the reference image andthe defect image are acquired for each detector image (S801 and S802),and the difference image is calculated by the difference imagecalculation unit 209 (S803).

The reference image is an image from which the circuit pattern similarto the defect image is observed and which does not include a defect. Thesemiconductor wafer utilizes a fact that a plurality of chips or partialregions manufactured so that the same circuit pattern is formed areincluded in the wafer. In this manner, it is possible to capture thereference image in the vicinity of the chip or the defect site adjacentto the chip including the defect. Alternatively, the reference image maybe generated by using the plurality of defect images obtained by imaginga location manufactured so that the same circuit pattern is formed, forexample, by calculating a weighted average. In addition, as disclosed inPTL 3, the reference image synthesized from the defect image may be usedby utilizing the periodicity of the circuit pattern. Furthermore, thereference image generated by SEM simulation based on design informationmay be used.

The difference image calculation unit 209 calculates the differencebetween the defect image and the reference image, thereby removing theshadow relating to the circuit pattern which appears in the same placeof the circuit pattern of both the defect image and the reference image.Accordingly, only the shadow relating to the defect site remains in thedifference image. If the number of the detector images is set to n, then-number of difference values per pixel is obtained. FIG. 9 illustratesan example in which this number is plotted as a scatter plot in then-dimensional space by the difference value distribution informationcalculation unit 210. There are as many axes as the detectors, andpoints are plotted as many as the number of pixels. However, FIG. 9illustrates only two dimensions relating to detectors A and B for thesake of simplified drawing.

In this example, the difference value distribution in the detector A ismore widely distributed than the detector B. This indicates that thedetector A includes more shadows of the defect than the detector B, andthus, the visibility of the detector A can be considered higher. Inaddition, it is possible to easily calculate a characteristic axis 903where dispersion is maximized when each plotted point is projected onthe axis, by using a method such as a principal component analysis. Thatis, the characteristic axis 903 is a first principal component axis anda characteristic axis 904 is a second principal component axis. Aprojection parameter with respect to the principal component axis isobtained. In this manner, it is possible to generate highly visiblemixed image.

Next, a mixing parameter calculation process (S702) performed in themixing parameter calculation unit 211 in the flow illustrated in FIG. 7and an image mixing process (S703) performed in the image mixing processunit 212 will be described. A mixing parameter is a generic name ofparameters in the image mixing process (S703). For example, a weightingfactor required when images are mixed with each other using the weightedaverage for the detector image is one of the mixing parameters. In theimage mixing process performed by the image mixing process unit 212,linear mixing may be performed on each of the detector images asexpressed in (Equation 1), or nonlinear mixing may be performed on eachof the detector images as expressed in (Equation 2). In (Equation 1) and(Equation 2), x_(i) (i=1, 2, 3, . . . , n) represents a detector imageset (n is the detector number), y_(j) (j=1, 2, 3, . . . , n) representsthe j-th mixed image, w_(i) represents the weighting factor, f(x_(i))represents a nonlinear function, and β represents an offset term. Inaddition, the nonlinear function f(x_(i)) may be the polynomialexpression or the sigmoid function.

Using the nonlinear function enables amplifications to vary according tothe pixel density value. Therefore, it is possible to suppress theamplification of noise components concentrated in a region where thepixel density value is low, or it is possible to suppress the densitysaturation of the circuit pattern having a high pixel density value.y _(j) =Σw _(i) x _(i)+β  (Equation 1)y _(j) =Σw _(i) f(x _(i))+β  (Equation 2)

In the mixing parameter calculation process (S702) performed by themixing parameter calculation unit 211, the weighting factor w_(i) foreach detector image is calculated, based on the analysis result of thedifference value distribution obtained in the defect informationextraction process (S701).

Description will be continued in more detail with reference to theexample in FIG. 9. Based on the inclination of the first principalcomponent axis and db/da, the weight w₁ of the detector A which servesas the projection parameter with respect to the principal component axismay be set to da, and the weight w₂ of the detector B may be set to db.Although FIG. 9 illustrates a case where the detector number n is 2, itis also possible to easily perform calculation in a case where thedetector number n is 3 or more. It is also possible to calculate themixing parameter of a second mixed image by using the second principalcomponent axis. In addition, whether to select linear mixing ornonlinear mixing as a mixing method may be determined by referring toexternal parameters stored in the recipe. Alternatively, the mixingmethods may be automatically switched therebetween in accordance withthe input image.

In the image mixing process (S703), based on the mixing parametercalculated by the mixing parameter calculation unit 211, the imagemixing process unit 212 mixes and outputs the detector images.

FIG. 17 is a view illustrating the input and the output of the imagemixing process (S703) performed by the image mixing process unit 212. Inthe example, the mixing parameter 1701 calculated in the mixingparameter calculation process (S702) by the mixing parameter calculationunit 211 is used. In the image mixing process (S703), the image mixingprocess unit 212 mixes five input images (1711 to 1715), and outputs twoimages (1721 and 1722). The input images 1711 to 1715 are obtained byprocessing signals respectively detected by the detectors 301 to 305.The number of images to be output may be determined as an externalparameter, or may be automatically calculated, based on a contributionratio obtained in the principal component analysis.

Hitherto, a method has been described in which in the defect informationextraction process step of S701, the mixing parameter is determinedusing the analysis result of the difference value distribution as thedefect information. However, the defect information is not limited tothe difference value distribution information.

As the other defect information extracted in the defect informationextraction process step of S701, a method for calculating an appearancecharacteristic amount of the defect site will be described withreference to FIG. 10. First, a defect region is recognized from thedetector image by using the defect region recognition unit 213 (S1001).As this method, it is possible to use the same method as the method forre-detecting the defect in ADR. This step may employ the method asdisclosed in PTL 2 and PTL 3, in which the density difference betweenthe defect image and the reference image is calculated so that a regionhaving a great density difference is extracted as a defect portion.

Next, the circuit pattern region recognition unit 213 is used so as torecognize a circuit pattern region from the detector image (S1002). Asthis method, as disclosed in PTL 7, the circuit pattern region and abackground region may be recognized using the pixel density distributioninformation, or the regions may be recognized using design information.

Based on the recognized defect region and the circuit pattern region asdescribed above, an appearance characteristic amount of the defect siteis calculated by the defect site appearance characteristic amountcalculation unit 215 (S1003). Here, the appearance characteristic of thedefect site means irregularity information obtained from the detectorimage, a direction of the defect, or a position relationship with thecircuit pattern. However, the appearance characteristic is not limitedthereto. For example, it is qualitatively evident that the defectappearing along the x-direction of the image is obvious in the detectorsarranged in the y-direction of the image. Therefore, in the mixingparameter calculation process (S702), a mixing parameter is calculatedusing the appearance characteristic of the defect site and acorrespondence table (FIG. 11) between the appearance characteristiccondition and the weighting factor, which is prepared in advance.

Specifically, in the correspondence table of FIG. 11, the weightingfactors of the detectors A to E for are determined depending on eachdefect characteristic of a defect site characteristic 1111, thecharacteristic corresponding to a type of the defect is selected, anaverage value of the weighting factors is obtained for each of thedetectors, and the average value is used as the weight. That is, in thecorrespondence table illustrated in FIG. 11, an item having a flag of 1in a condition coincidence determination column 1113 (in a case of FIG.11, a defect whose defect site characteristic 1111 is #2 and a defect inthe groove bottom of the color pattern in the X-direction of #3) isextracted as an item coincident with the condition. In this manner, aweighted average 1114 (in a case of FIG. 11, a value obtained in such away that a value obtained by adding the weighting factors in thevertical axis direction for each detector in a weighting factor column1112 is divided by the number of the added weighting factors) may be setas a weighting factor w_(i) of the detector image obtained by eachdetector.

Hitherto, a method has been described in which the difference valuedistribution information and the defect site appearance characteristicamount are extracted as the defect information in the defect informationextraction process (S701) so as to set the mixing parameter. The twopieces of information described above are not exclusive. For example,both pieces of information can be complementarily used by averaging theweighting factors calculated using a weighting factor correspondencetable between the weighting factors calculated using the differencevalue distribution information described with reference to FIG. 9 andthe appearance characteristic condition described with reference to FIG.11. In addition, the defect information may be any information usefulfor determining the visibility of the defect portion in the mixed image,but the defect information is not limited thereto. For example, it isalso possible to utilize the information used when a defect inspectiondevice detects the defect.

Hitherto, a method has been described in which the mixing parameter iscalculated by using all of the detector images so as to mix the images.However, the mixing parameter may be calculated and the images may bemixed using only the previously selected detector image. Alternatively,the plurality of detectors may be grouped so as to calculate the mixingparameter and to mix the images. For example, the detector for mainlydetecting the reflected electron and the detector for mainly detectingthe secondary electron are separately grouped. In this manner, the mixedimage generated using the above-described method from the image of thedetector which mainly detects the reflected electron, and the mixedimage generated from the image of the detector which mainly detects thesecondary electron may be respectively output.

Finally, a mixed image output (S607) will be described. In this process,the mixed image is output to the input/output terminal 113 or the imagestorage unit 205. Alternatively, the mixed image may be output to anexternal device via the network interface unit 107. In this case, themixed image is output together the mixing parameter. The mixingparameter may be written in an incidental information file of the outputimage, or may be overlaid and displayed on the image.

FIGS. 12A to 12C illustrate an example in which the weighting factorsfor each detector in the mixing parameters are overlaid and displayed onimages 1201 to 1203 in the mixed image output (S607). The images 1201 to1203 in FIGS. 12A to 12C correspond to an image 1721 or 1722 obtained insuch a way that the image mixing process unit 212 performs the imagemixing process in S703 on detector images 1711 to 1715 detected by eachdetector as described in FIG. 17 by using the mixing parameter 1701.

As a way to overlay and display the weighting factors for each detectorin the image mixing process on the image 1201 to 1203 obtained byperforming the image mixing process, character information 1204 may beoutput as illustrated in FIG. 12A. Alternatively, as illustrated in FIG.12B, a radar chart 1205 may be output. Alternatively, a bar graph 1206may be output as illustrated in FIG. 12C. As long as the output shows amagnitude relationship of the weighting factors between the detectors,any output method may be employed. In particular, as illustrated in FIG.12B, an axis 1207 of the radar chart 1205 is caused to be coincidentwith the actual direction of the detector. In this manner, the magnituderelationship of the weighting factors with respect to the detectiondirection becomes intuitive, thereby facilitating the understanding ofthe irregularity information. In addition to the weighting factor, it isalso possible to output a mixing method.

As described above, various electrons having different emission anglesor energies generated in the sample are detected by the plurality ofdetectors, and the difference value distribution information or theappearance characteristic amount of the defect site is extracted as thedefect information by using the detector image. Based on the extracteddefect information, the mixing parameter is automatically calculated,the images are mixed based on the calculated mixing parameter, and themixed image is output together with the mixing parameter. In thismanner, a highly visible image of various defects can be output, therebyenabling a user to reduce the burden when the user observes the images.

In this way, various electrons having different emission angles oremission energies generated in the sample are detected by the pluralityof detectors, and the difference value distribution information or theappearance characteristic amount of the defect site is extracted as thedefect information by using the detector image. Based on the extracteddefect information, the mixing parameter is automatically calculated,the images are mixed based on the calculated mixing parameter, and themixed image is output together with the mixing parameter. In thismanner, the highly visible image of various defects can be output.

Embodiment 2

In Embodiment 1, a method for outputting the highly visible image ofvarious defects has been described. In Embodiment 2, a method forgenerating and outputting a highly visible image of not only the defectbut also the circuit pattern will described.

A device configuration according to the present embodiment is the sameas that illustrated in FIGS. 1 and 2 in Embodiment 1. In addition, amain flow of the observation process is also the same as the flow of theobservation process described with reference to FIG. 6. A differentpoint is a processing method of the mixed image generation process(S606). Hereinafter, only elements different from those in Embodiment 1will be described.

In the image mixing method according to the present embodiment, thedetector image is discriminated into a defect region and a region otherthan the defect (background region), the mixing parameter is calculatedfor each region, and the images are mixed using the mixing parameterswhich are different from each other in each region. A specificprocessing flow will be described with reference to FIG. 13.

First, in the region discrimination process (S1301), the defect regionis extracted from the detector image by the defect region recognitionunit 213, and is discriminated into the defect region and the regionother than the defect region. A method for extracting the defect regionmay be the same as the method described in Embodiment 1. In a case wherea plurality of defects are present in the image, each defect may bediscriminated as a separate defect region. Alternatively, the circuitpattern region recognition unit 214 may be used so as to discriminatethe background region into the circuit pattern region.

FIG. 14A illustrates a detector image 1410, and FIG. 14B illustrates anexample of a region discrimination result 1420. In the detector image1410 of FIG. 14A, a circuit pattern 1411 of an upper layer formed alongthe y-direction of the image, a circuit pattern 1412 of a lower layerformed along the x-direction of the image, an two defects 1413 and 1414are imaged. FIG. 14B illustrates an example of the region discriminationresult 1420, the background region is discriminated into an upper layercircuit pattern region 1421 and a lower layer circuit pattern region1422, and two regions such as a region 1423 and a region 1424 areextracted and discriminated as the defect region.

After the region is discriminated, the mixing parameter is calculatedindependently for each region. With regard to the background region, thedifference value distribution information calculation unit 210 analyzesthe density value distribution of each detector in a background densityvalue distribution analysis process (S1302). In this process, thedifference value distribution information calculation unit 210 describedin Embodiment 1 analyzes the difference value distribution by using adensity value for each background region discriminated in a regiondiscrimination process (S1301). Similarly to the analysis of thedifference value distribution in Embodiment 1, the characteristic axiswhere the dispersion of the density value is maximized is calculatedusing the principal component analysis.

Next, based on the analysis result of the background region densityvalue distribution of S1302 in the difference value distributioninformation calculation unit 210, the mixing parameter is calculated bythe mixing parameter calculation unit 211 (S1303). This process may alsoemploy the same method as the mixing parameter calculation method basedon the difference value distribution information obtained by the mixingparameter calculation unit 211 described with reference to FIG. 8 inEmbodiment 1. That is, in S1302, the mixing parameter is set based onthe inclination of the principal component axis obtained by analyzingthe background region density value distribution. In addition, asdisclosed in PTL 6, the mixing parameter may be calculated based on theedge direction of the circuit pattern. Furthermore, the mixing parametermay be calculated based on the analysis result of the background densityvalue distribution and the edge direction of the circuit pattern.

With regard to the defect region, the mixing parameter may be calculatedusing the method described in Embodiment 1. That is, the defectinformation may be extracted by the defect information extraction unit208 (S1304), and the mixing parameter calculation unit 211 may calculatethe mixing parameter, based on the extracted defect information (S1305).As illustrated in a table 1500 in FIG. 15, the mixing parameter(weighting factor 1502) calculated for each region is stored in thestorage unit 103 in association with a region 1501. In the exampleillustrated in FIG. 15, numbers 1421 to 1424 in the column of the region1501 correspond to regions 1421 to 1424 in FIG. 14B.

If the mixing parameter for each region is completely calculated byrepeating processes of Loop 1, the image mixing process unit 212subsequently mixes the images for each region by performing an imagemixing process (S1306). In this case, in order to reduce thediscontinuity caused by the difference in the mixing parametersoccurring at the boundary of the region, the discriminated region may beexpanded so as to calculate a density weighted average for theoverlapping region. Alternatively, the images may be mixed after theweighted average of the mixing parameters is calculated.

According to the above-described method, it is possible to output a highvisible image of not only the defect site but also the circuit pattern.

Embodiment 3

In Embodiment 1 and Embodiment 2, a method has been described in whichthe mixing parameter is calculated using the detector image so as to mixthe highly visible image of the defect site and the circuit pattern. Inthe present embodiment, a method will be described in which a highlyvisible observation image is obtained for ADR.

ADR is a function to automatically collect observation images, based ondefect position coordinates output by another defect inspection device.The defect position coordinates output by the inspection device includean error. Accordingly, ADR is provided with a function to re-detect thedefect from an image obtained by imaging the defect position coordinateswith low magnification, and to mainly image the re-detected defectposition as a high magnification image for observation. In the presentembodiment, a method will be described in which the mixing parameter iscalculated from a low magnification image so as to be used in mixing theimages for a high magnification image.

A device configuration according to the present embodiment is the sameas the device configuration illustrated in FIGS. 1 and 2 described inEmbodiment 1 and Embodiment 2. FIG. 16 illustrates a defect observationflow according to the present embodiment.

First, the wafer 108 serving as an observation target is loaded on thestage 109 (S1601), a recipe storing image capturing conditions (anacceleration voltage, a probe current, and the number of added frames)and image processing conditions is read from the recipe storage unit 206so as to set an electron optical system of SEM 101 in accordance withthe read conditions (S1602). Next, the defect position coordinatesstored in the coordinate storage unit 207 and output by the defectinspection device is read (S1603).

The subsequent processes S1604 to S1611 are performed for therespectively read defect position coordinates. First, the stage 109 ismoved using the stage control unit 202 so that the defect positioncoordinates are included in the imaging field of view of the electronoptical system of SEM 101 (step S1604). Next, the sample wafer 108 isimaged at low magnification in which a size of the field of view (lengthof one side of the sample surface in the imaging field of view of theelectron optical system of SEM 101) is approximately 10 to 3 μm (S1605).Next, the defect is re-detected from the field of view of the capturedlow magnification image of the sample wafer 108 (S1606), the mixingparameter is calculated using the low magnification image (S1607), andthe mixed image of the low magnification images is generated (S1608).Next, an image of mainly the defect position redetected from the lowmagnification image is captured at high magnification in which a size ofthe field of view size is approximately 3 to 0.5 μm (S1609), thehigh-magnification images are mixed using the mixing parametercalculated in Process S1607 (S1610), and the mixed low-magnificationimage and high-magnification image are output (S1611).

With regard to the mixing parameter calculation process (S1607), themethod described in Embodiment 1 and Embodiment 2 may be used. Inaddition, after the high magnification image is captured, the mixingparameter may be calculated using the high magnification image, and themixing parameter of the high magnification image may be calculated byusing the mixing parameter together with the mixing parameter calculatedfrom the low magnification image.

According to the above-described method, the visibility of the mixedimage of the low magnification images is similar to the visibility ofthe mixed image of the high magnification images. Accordingly, it ispossible to obtain a highly visible high magnification image.

INDUSTRIAL APPLICABILITY

The present invention is applicable to a sample observation deviceincluding means for outputting an highly visible image of a defect or acircuit pattern by using images obtained from a plurality of detectorsincluded in a charged particle microscope which observes the defect orthe circuit pattern appearing while semiconductor wafers aremanufactured in manufacturing lines of the semiconductor wafers.

REFERENCE SIGNS LIST

-   -   101 SCANNING ELECTRON MICROSCOPE (SEM)    -   108 WAFER SAMPLE    -   112 IMAGING UNIT    -   205 IMAGE STORAGE UNIT    -   206 RECIPE STORAGE UNIT    -   207 COORDINATE STORAGE UNIT    -   208 DEFECT INFORMATION EXTRACTION UNIT    -   209 DIFFERENCE IMAGE CALCULATION UNIT    -   210 DIFFERENCE VALUE DISTRIBUTION INFORMATION CALCULATION UNIT    -   211 MIXING PARAMETER CALCULATION UNIT    -   212 IMAGE MIXING PROCESS UNIT    -   213 DEFECT REGION RECOGNITION UNIT    -   214 CIRCUIT PATTERN REGION RECOGNITION UNIT    -   215 DEFECT SITE APPEARANCE CHARACTERISTIC AMOUNT CALCULATION        UNIT    -   301 to 305 CHARGED PARTICLE DETECTOR

The invention claimed is:
 1. A sample observation method for observing asample by using a charged particle microscope, the method comprising:causing a plurality of detectors arranged at different positions fromthe sample to detect a secondary electron or a reflected electrongenerated from the sample by irradiating and scanning the sample with acharged particle beam; extracting defect information on the sample froman image of the sample which is generated by each of the plurality ofdetectors; calculating a mixing parameter of the image based on thedefect information; generating a mixed image by using the mixingparameter so as to mix a plurality of images of the sample with eachother for each of the plurality of detectors, which are obtained in sucha way that each of the plurality of detectors arranged at the differentpositions detects the secondary electron or the reflected electron; andoutputting the generated mixed image.
 2. The sample observation methodaccording to claim 1, wherein the mixed image is generated by mixing theplurality of images of the sample for each of the plurality ofdetectors, which are obtained in such a way that each of the pluralityof detectors arranged at the different positions detects the secondaryelectron or the reflected electron, so as to output an image whosevisibility of a defect site or a pattern on the sample is furtherimproved than the image of the sample which is obtained by each of theplurality of detectors.
 3. The sample observation method according toclaim 1, wherein in order to generate the mixed image by mixing theplurality of images of the sample for each of the plurality ofdetectors, which are obtained in such a way that each of the pluralityof detectors arranged at the different positions detects the secondaryelectron or the reflected electron, the images are mixed with each otherby adding a weight to each of the plurality of images of the sample foreach of the plurality of detectors.
 4. The sample observation methodaccording to claim 1, wherein in order to generate the mixed image bymixing the plurality of images of the sample for each of the pluralityof detectors, the images are mixed with each other by changing a weightof each of the plurality of images of the sample in accordance with atype of observation target patterns or defects on the sample.
 5. Thesample observation method according to claim 1, wherein the mixed imageobtained by mixing the plurality of images of the sample for each of theplurality of detectors, and information relating to a weight of theplurality of images of the sample for each of the plurality of detectorsin the mixed image are displayed on a screen.
 6. A sample observationmethod for observing a sample by using a charged particle microscope,the method comprising: causing a plurality of detectors arranged atdifferent positions from the sample to detect a secondary electron or areflected electron generated from a first region of the sample byirradiating and scanning the first region with a charged particle beam;generating a plurality of images of the first region for each of theplurality of detectors, based on a signal obtained by causing each ofthe plurality of detectors arranged at the different positions to detectthe secondary electron or the reflected electron; calculating a mixingparameter serving as each weight of the plurality of generated images ofthe first region for each of the plurality of detectors; causing theplurality of detectors arranged at the different positions from thesample to detect the secondary electron or the reflected electrongenerated from a second region by irradiating and scanning the secondregion inside the first region on the sample with the charged particlebeam; generating a plurality of images of the second region for each ofthe plurality of detectors with higher magnification than that of theplurality of images of the first region, based on a signal obtained bycausing each of the plurality of detectors arranged at the differentpositions to detect the secondary electron or the reflected electron;generating a mixed image with high magnification in such a way that theplurality of generated images of the second region are mixed with eachother using the calculated mixing parameter; and outputting thegenerated mixed image with high magnification, and wherein the generatedmixed image with high magnification is displayed on a screen togetherwith information relating to the weight.
 7. The sample observationmethod according to claim 6, wherein the mixing parameter is calculatedusing defect information extracted from the plurality of generatedimages of the first region.
 8. A sample observation device for observinga sample by using a charged particle microscope, the device comprising:the charged particle microscope that includes a plurality of detectorsarranged at different positions from the sample so that the plurality ofdetectors detect a secondary electron or a reflected electron generatedfrom the sample by irradiating and scanning the sample with a chargedparticle beam; an image generation unit that generates images of thesample for each of the plurality of detectors, based on a signalobtained by causing each of the plurality of detectors arranged at thedifferent positions of the charged particle microscope to detect thesecondary electron or the reflected electron; a mixed image generationunit that generates a mixed image by mixing the images of the samplewhich are generated by the image generation unit for each of theplurality of detectors; and a display unit that displays the mixed imagegenerated by the mixed image generation unit, and wherein the displayunit displays the mixed image obtained by adding a weight theretotogether with information relating to the weight.
 9. The sampleobservation device according to claim 8, wherein the mixed imagegeneration unit generates the mixed image in such a way that the imagesare mixed with each other by adding a weight to each of the images ofthe sample for each of the plurality of detectors.
 10. The sampleobservation device according to claim 8, wherein the mixed imagegeneration unit mixes the images with each other by adding a weight toeach of the plurality of images of the sample for each of the pluralityof detectors in accordance with a type of observation target patterns ordefects on the sample.
 11. The sample observation device according toclaim 8, further comprising: a defect information extraction unit; and amixing parameter calculation unit, wherein the defect informationextraction unit extracts defect information on the sample from the imageof the sample which is generated by each of the plurality of detectorsarranged at the different positions, wherein the mixing parametercalculation unit calculates a mixing parameter serving as a weight ofthe image of the sample for generating the mixed image in the mixedimage generation unit, and wherein the mixed image generation unit mixesthe images by adding the weight to the image generated by the imagegeneration unit using the mixing parameter calculated by the mixingparameter calculation unit for each of the plurality of detectorsarranged at the different positions.
 12. The sample observation deviceaccording to claim 8, wherein the mixed image generation unit mixes theimages with each other by adding a weight to the image of the sample foreach of the plurality of detectors arranged at the different position,which is generated by the image generation unit, so as to generate animage whose visibility of a defect site or a pattern on the sample isfurther improved than the image of the sample which is obtained by eachof the plurality of detectors.
 13. The sample observation methodaccording to claim 5, wherein the information relating to the weight ofthe plurality of the images is overlaid and displayed on the generatedmixed image.
 14. The sample observation method according to claim 6,wherein the information relating to the weight of the plurality of theimages is overlaid and displayed on the generated mixed image.
 15. Thesample observation device according to claim 8, wherein the display unitoverlays and displays the information relating to the weight of theplurality of the images on the generated mixed image.